Route risk mitigation

ABSTRACT

A method is disclosed for mitigating the risks associated with driving by assigning risk values to road segments and using those risk values to select less risky travel routes. Various approaches to helping users mitigate risk are presented. A computing device is configured to generate a database of risk values. That device may receive accident information, geographic information, vehicle information, and other information from one or more data sources and calculate a risk value for the associated road segment. Subsequently, the computing device may provide the associated risk value to other devices. Furthermore, a personal navigation device may receive travel route information and use that information to retrieve risk values for the road segments in the travel route. An insurance company may use this information to determine whether to adjust a quote or premium of an insurance policy. This and other aspects relating to using geographically encoded information to promote and reward risk mitigation are disclosed.

RELATED APPLICATION

This application is a divisional of U.S. patent application Ser. No.12/118,021, filed May 9, 2008, issued Dec. 10, 2013 as U.S. Pat. No.8,606,512, which claims priority to U.S. Provisional Patent ApplicationNo. 60/917,169 filed May 10, 2007. Both of the aforementioned areincorporated by reference in their entirety herein.

TECHNICAL FIELD

Aspects of the invention relate generally to risk mitigation. Moreparticularly, aspects of the invention relate to using geographicallyencoded information to promote and/or reward risk mitigation.

DESCRIPTION OF THE RELATED ART

Although insurers may vary insurance premiums based on garaging location(by state, county, etc.), there is a need in the art for enhancedsystems and methods to better account for variations in a location-basedrisk to vehicles and subsequently acting accordingly. For example, someinsurers use location-based technology such as GPS (global positioningsatellites) to monitor the location of vehicles. Nevertheless, there isa need in the art for a technique for estimating the risk associatedwith a route using the various aspects disclosed by the presentinvention. Therefore, there is a benefit in the art for an enhancedmethod and device for calculating a risk for a road segment and using itto, among other things, mitigate risk.

SUMMARY

Aspects of the invention overcome problems and limitations of the priorart by providing a method for mitigating the risks associated withdriving by assigning risk values to road segments and using those riskvalues to select less risky travel routes.

Various approaches to helping users mitigate risk are presented. Inaccordance with aspects of the invention, a computing system isdisclosed for generating a data store (e.g., database) of risk values.The system may receive various types of information, including but notlimited to, accident information, geographic information, and vehicleinformation, from one or more data sources. The system calculates a riskvalue for an associated road segment. Subsequently, the computing systemmay provide the associated risk value when provided with locationinformation (and/or other information) for the road segment.

In an alternate embodiment in accordance with aspects of the invention,a personal navigation device, mobile device, and/or personal computingdevice may communicate, directly or indirectly, with the system'sdatabase of risk values. The system may receive travel route informationand use that information to retrieve risk values for the associated roadsegments in the travel route. The system may send a compilation of therisk values to the device for display on a screen of the device or forrecording in memory. The system may also aggregate risk values and forma score that is then sent for display on the screen of the device orsent for recording in a memory. The contents of memory may also beuploaded to a data store for use by, e.g., insurance companies, todetermine whether to adjust a quote or premium of an insurance policy.

In an alternate embodiment in accordance with aspects of the invention,a personal navigation device, mobile device, and/or personal computingdevice may communicate, directly or indirectly, with the system'sdatabase of risk values. The system may receive regional locationinformation and retrieve the risk values for road segments within theassociated region and send the associated information to the device forrecording into memory. The device may receive travel route informationand query the memory for the associated risk values. The risk values maybe sent for display on the device or for recording in memory. Thecontents of memory may also be uploaded to a system data store for useby, e.g., insurance companies, to determine whether to adjust a quote orpremium of an insurance policy.

In yet another embodiment, in accordance with aspects of the invention,a personal navigation device, mobile device, and/or personal computingdevice may access the database of risk values to assist in identifyingand presenting alternate lower-risk travel routes. The driver may selectamong the various travel routes presented, taking into account one ormore factors such as a driver's tolerance for risk and/or desire tolower the cost of insurance. These factors may be saved in memorydesignating the driver's preferences. Depending on the driver'sselection/preferences, the cost or other aspects of the vehicle'sinsurance coverage may be adjusted accordingly for either the currentinsurance policy period or a future insurance policy period.

The details of these and other embodiments of the invention are setforth in the accompanying drawings and description below. Other featuresand advantages of aspects of the invention will be apparent from thedescription and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Aspects of the invention may take physical form in certain parts andsteps, embodiments of which will be described in detail in the followingdescription and illustrated in the accompanying drawings that form apart hereof, wherein:

FIG. 1 depicts an illustrative operating environment in accordance withaspects of the invention;

FIG. 2 depicts illustrative steps for calculating the risk value of aroute segment by applying actuarial and/or statistical methods inaccordance with aspects of the invention;

FIG. 3 depicts illustrative steps for determining and providing riskvalues to a computing device in accordance with aspects of theinvention;

FIG. 4 depicts illustrative steps for calculating the risk value of atravel route in accordance with aspects of the invention; and

FIG. 5 depicts illustrative steps for providing an insurance policybased on risk consumption in accordance with aspects of the invention.

It will be apparent to one skilled in the art after review of theentirety disclosed that the steps illustrated in the figures listedabove may be performed in other than the recited order, and that one ormore steps illustrated in these figures may be optional.

DETAILED DESCRIPTION

In accordance with aspects of the invention, a new set of pricing tiersare disclosed herein for enabling safe driving and lower rates forinsurance policy customers. In addition, various approaches to helpingusers mitigate risk are presented. In accordance with aspects of theinvention, a computing device is disclosed for generating risk values ina data store. The system may receive various types of information,including but not limited to, accident information, geographicinformation, and vehicle information, from one or more data sources andcalculate a risk value for associated road segments. Subsequently, thecomputing device may provide the associated risk value when providedwith location information for a road segment such as regional locationinformation and/or other information.

In an alternate embodiment in accordance with aspects of the invention,a personal navigation device, mobile device, and/or personal computingdevice may communicate with the database of risk values. The devices mayreceive information about a travel route and use that information toretrieve risk values for road segments in the travel route. Theaggregate of the risk values is sent for display on a screen of thedevice or for recording in memory of the device. The contents of memorymay also be uploaded to a data store for use by, e.g., insurancecompanies, to determine whether to adjust a quote for insurance coverageor one or more aspects of current insurance coverage such as premium,specific coverages, specific exclusions, rewards, special terms, etc.

In yet another embodiment, in accordance with aspects of the invention,a personal navigation device, mobile device, and/or personal computingdevice may access the database of risk values to assist in identifyingand presenting alternate low-risk travel routes. The driver may selectamong the various travel routes presented, taking into account his/hertolerance for risk. Depending on the driver's selection, the vehicle'sinsurance policy may be adjusted accordingly, for either the currentinsurance policy or a future insurance policy.

Referring to FIG. 1, an example of a suitable operating environment inwhich various aspects of the invention may be implemented is shown inthe architectural diagram of FIG. 1. The operating environment is onlyone example of a suitable operating environment and is not intended tosuggest any limitation as to the scope of use or functionality of theinvention. The operating environment may be comprised of one or moredata sources 104, 106 in communication with a computing device 102. Thecomputing device 102 may use information communicated from the datasources 104, 106 to generate values that may be stored in a conventionaldatabase format. In one embodiment, the computing device 102 may be ahigh-end server computer with one or more processors 114 and memory 116for storing and maintaining the values generated. The memory 116 storingand maintaining the values generated need not be physically located inthe computing device 102. Rather, the memory (e.g., ROM, flash memory,hard drive memory, RAID memory, etc.) may be located in a remote datastore (e.g., memory storage area) physically located outside thecomputing device 102, but in communication with the computing device102.

A personal computing device 108 (e.g., a personal computer, tablet PC,handheld computing device, personal digital assistant, mobile device,etc.) may communicate with the computing device 102. Similarly, apersonal navigation device 110 (e.g., a global positioning system (GPS),geographic information system (GIS), satellite navigation system, mobiledevice, other location tracking device, etc.) may communicate with thecomputing device 102. The communication between the computing device 102and the other devices 108, 110 may be through wired or wirelesscommunication networks and/or direct links. One or more networks may bein the form of a local area network (LAN) that has one or more of thewell-known LAN topologies and may use a variety of different protocols,such as Ethernet. One or more of the networks may be in the form of awide area network (WAN), such as the Internet. The computing device 102and other devices (e.g., devices 108, 110) may be connected to one ormore of the networks via twisted pair wires, coaxial cable, fiberoptics, radio waves or other media. The term “network” as used hereinand depicted in the drawings should be broadly interpreted to includenot only systems in which devices and/or data sources are coupledtogether via one or more communication paths, but also stand-alonedevices that may be coupled, from time to time, to such systems thathave storage capability.

In another embodiment in accordance with aspects of the invention, apersonal navigation device 110 may operate in a stand-alone manner bylocally storing some of the database of values stored in the memory 116of the computing device 102. For example, a personal navigation device110 (e.g., a GPS in an automobile) may be comprised of a processor,memory, and/or input devices 118/output devices 120 (e.g., keypad,display screen, speaker, etc.). The memory may be comprised of anon-volatile memory that stores a database of values used in calculatingan estimated route risk for identified routes. Therefore, the personalnavigation device 110 need not communicate with a computing device 102located at, for example, a remote location in order to calculateidentified routes. Rather, the personal navigation device 110 may behavein a stand-alone manner and use its processor to calculate route riskvalues of identified routes. If desired, the personal navigation device110 may be updated with an updated database of values after a period oftime (e.g., an annual patch with new risk values determined over theprior year).

In yet another embodiment in accordance with aspects of the invention, apersonal computing device 108 may operate in a stand-alone manner bylocally storing some of the database of values stored in the memory 116of the computing device 102. For example, a personal computing device108 may be comprised of a processor, memory, input device (e.g., keypad,CD-ROM drive, DVD drive, etc.), and output device (e.g., display screen,printer, speaker, etc.). The memory may be comprised of CD-ROM mediathat stores values used in calculating an estimated route risk for anidentified route. Therefore, the personal computing device 108 may usethe input device to read the contents of the CD-ROM media in order tocalculate a value for the identified route. Rather, the personalcomputing device 108 may behave in a stand-alone manner and use itsprocessor to calculate a route risk value. If desired, the personalcomputing device 108 may be provided with an updated database of values(e.g., in the form of updated CD-ROM media) after a period of time. Oneskilled in the art will appreciate that personal computing device 108,110, 112 need not be personal to a single user; rather, they may beshared among members of a family, company, etc.

The data sources 104, 106 may provide information to the computingdevice 102. In one embodiment in accordance with aspects of theinvention, a data source may be a computer which contains memory storingdata and is configured to provide information to the computing device102. Some examples of providers of data sources in accordance withaspects of the invention include, but are not limited to, insurancecompanies, third-party insurance data providers, government entities,state highway patrol departments, local law enforcement agencies, statedepartments of transportation, federal transportation agencies, trafficinformation services, road hazard information sources, constructioninformation sources, weather information services, geographicinformation services, vehicle manufacturers, vehicle safetyorganizations, and environmental information services. For privacyprotection reasons, in some embodiments of the invention, access to theinformation in the data sources 104, 106 may be restricted to onlyauthorized computing devices 102 and for only permissible purposes. Forexample, access to the data sources 104, 106 may be restricted to onlythose persons/entities that have signed an agreement (e.g., anelectronic agreement) acknowledging their responsibilities with regardto the use and security to be accorded this information.

The computing device 102 uses the information from the data sources 104,106 to generate values that may be used to calculate an estimated routerisk. Some examples of the information that the data sources 104, 106may provide to the computing device 102 include, but are not limited to,accident information, geographic information, and other types ofinformation useful in generating a database of values for calculating anestimated route risk.

Some examples of accident information include, but are not limited to,loss type, applicable insurance coverage(s) (e.g., bodily injury,property damage, medical/personal injury protection, collision,comprehensive, rental reimbursement, towing), loss cost, number ofdistinct accidents for the segment, time relevancy validation, cause ofloss (e.g., turned left into oncoming traffic, ran through red light,rear-ended while attempting to stop, rear-ended while changing lanes,sideswiped during normal driving, sideswiped while changing lanes,accident caused by tire failure (e.g., blow-out), accident caused byother malfunction of car, rolled over, caught on fire or exploded,immersed into a body of water or liquid, unknown, etc.), impact type(e.g., collision with another automobile, collision with cyclist,collision with pedestrian, collision with animal, collision with parkedcar, etc.), drugs or alcohol involved, pedestrian involved, wildlifeinvolved, type of wildlife involved, speed of vehicle at time ofincident, direction the vehicle is traveling immediately before theincident occurred, date of incident, time of day, night/day indicator(i.e., whether it was night or day at the time of the incident),temperature at time of incident, weather conditions at time of incident(e.g., sunny, downpour rain, light rain, snow, fog, ice, sleet, hail,wind, hurricane, etc.), road conditions at time of incident (e.g., wetpavement, dry pavement, etc.), and location (e.g., geographiccoordinates, closest address, zip code, etc.) of vehicle at time ofincident.

Accident information associated with vehicle accidents may be stored ina database format and may be compiled per segment. One skilled in theart will understand that the term segment may be interchangeably used todescribe a road segment, intersection, round about, bridge, tunnel,ramp, parking lot, railroad crossing, or other feature that a vehiclemay encounter along a route.

Time relevancy validation relates to the relevancy of historicalaccident information associated with a particular location. Timerelevancy validation information may be dynamically created by comparingthe time frames of accident information to the current date. Forexample, if a location or route had many collisions prior to five yearsago but few since, perhaps a road improvement reduced the risk (such asadding a traffic light). Time relevancy information may be generatedremotely and transmitted by a data source 104, 106 to the computingdevice 102 like other information. Alternatively, time relevancyinformation may be calculated at the computing device 102 using otherinformation transmitted by a data source 104, 106. For example, theappropriateness of historical information may be related to the timeframe into which the information belongs. Examples of time frames mayinclude, but are not limited to, less than 1 year ago, 1 year ago, 2years ago, 3 years ago, 4 years ago, 5 to 10 years ago, and greater than10 years ago. In one embodiment, the more recent the historicalinformation, the greater weight is attributed to the information.

Some examples of geographic information include, but are not limited to,location information and attribute information. Examples of attributeinformation include, but are not limited to, information aboutcharacteristics of a corresponding location described by some locationinformation: posted speed limit, construction area indicator (i.e.,whether location has construction), topography type (e.g., flat, rollinghills, steep hills, etc.), road type (e.g., residential, interstate,4-lane separated highway, city street, country road, parking lot, etc.),road feature (e.g., intersection, gentle curve, blind curve, bridge,tunnel), number of intersections, whether a roundabout is present,number of railroad crossings, whether a passing zone is present, whethera merge is present, number of lanes, width of road/lanes, populationdensity, condition of road (e.g., new, worn, severely damaged withsink-holes, severely damaged with erosion, gravel, dirt, paved, etc.),wildlife area, state, county, and/or municipality. Geographicinformation may also include other attribute information about roadsegments, intersections, bridges, tunnels, railroad crossings, and otherroadway features.

Location information for an intersection may include the latitude andlongitude (e.g., geographic coordinates) of the geometric center of theintersection. The location may be described in other embodiments using aclosest address to the actual desired location or intersection. Theintersection (i.e., location information) may also include informationthat describes the geographic boundaries, for example, of theintersection which includes all information that is associated within acircular area defined by the coordinates of the center of theintersection and points within a specified radius of the center. Inanother example of location information, a road segment may be definedby the latitude and longitude of its endpoints and/or an area defined bythe road shape and a predetermined offset that forms a polygon. Segmentsmay comprise intersections, bridges, tunnels, rail road crossings orother roadway types and features. Those skilled in the art willrecognize that segments can be defined in many ways without departingfrom the spirit of this disclosed invention.

Some examples of vehicle information include, but are not limited to,information that describes vehicles that are associated with incidents(e.g., vehicle accidents, etc.) at a particular location (e.g., alocation corresponding to location information describing a segment,intersection, etc.) Vehicle information may include vehicle make,vehicle model, vehicle year, and age. Vehicle information may alsoinclude information collected through one or more in-vehicle devices orsystems such as an event data recorder (EDR), onboard diagnostic system,or global positioning satellite (GPS) device; examples of thisinformation include speed at impact, brakes applied, throttle position,direction at impact. As is clear from the preceding examples, vehicleinformation may also include information about the driver of a vehiclebeing driven at the time of an incident. Other examples of driverinformation may include age, gender, marital status, occupation, alcohollevel in blood, credit score, distance from home, cell phone usage(i.e., whether the driver was using a cell phone at the time of theincident), number of occupants.

In one embodiment in accordance with aspects of the invention, a datasource 104 may provide the computing device 102 with accidentinformation that is used to generate values (e.g., create new valuesand/or update existing values). The computing device 102 may use atleast part of the received accident information to calculate a value,associate the value with a road segment (or other location information),and store the value in a database format. One skilled in the art willappreciate, after thorough review of the entirety disclosed herein, thatthere may be other types of information that may be useful in generatinga database of values for use in, among other things, calculating anestimated route risk.

For example, in accordance with aspects of the invention, a data source104 may provide the computing device 102 with geographic informationthat is used to generate new roadway feature risk values in a databaseof risk values and/or update existing risk values; where the roadwayfeature may comprise intersections, road segments, tunnels, bridges, orrailroad crossings. Attributes associated with roadways may also be usedin part to generate risk values. The computing device 102 may use atleast part of the received geographic information to calculate a value,associate the value with a road segment (or other location information),and store the value in a database format. Numerous examples ofgeographic information were provided above. For example, a computingdevice 102 may receive geographic information corresponding to a roadsegment comprising accident information and roadway feature informationand then calculate a risk value. Therefore, when calculating a riskvalue, the system may use, in one example, the geographic informationand the accident information (if any accident information is provided).In alternative embodiments in accordance with aspects of the invention,the computing device may use accident information, geographicinformation, vehicle information, and/or other information, either aloneor in combination, in calculating risk values in a database format.

The values generated by the computing device 102 may be associated witha road segment containing the accident location and stored in a datastore. Similar to a point of interest (POI) stored in GPS systems, apoint of risk (POR) is a road segment or point on a map that has riskinformation associated with it. Points of risk may arise becauseincidents (e.g., accidents) have occurred at these points before. Inaccordance with aspects of the invention, the road segment may be apredetermined length (e.g., ¼ mile) on a stretch of road. Alternatively,road segments may be points (i.e., where the predetermined length isminimal) on a road. Furthermore, in some embodiments, road segment mayinclude one or more different roads that are no farther than apredetermined radius from a road segment identifier. Such an embodimentmay be beneficial in a location, for example, where an unusually largenumber of streets intersect, and it may be impractical to designate asingle road for a road segment.

Referring to FIG. 2, in accordance with aspects of the invention, acomputing device 102 may receive accident information (in step 202),geographic information (in step 204), and/or vehicle information (instep 206). The computing device 102 may calculate (in step 212) the riskvalue for a road segment (or point of risk) by applying actuarialtechniques to the information that may be received from data sources104, 106. In one embodiment, the computing device 102 receives andstores the accident information in a data store with thelatitude/longitude and time of the incident. The accident data isassociated with a location and combined with other accident dataassociated with the same location (in step 210). Applying actuarialand/or statistical modeling techniques involving multiple predictors,such as generalized linear models and non-linear models, a risk valuemay be calculated (212), and the calculated risk value may be recordedin memory (116) (in step 214). The multiple predictors involved in thestatistical model used to calculate a risk value may include accidentinformation, geographic information, and vehicle information.Associating the risk value (in step 208) with a line segment and/orpoint which best pinpoints the area of the road in which the incident(s)occurred may be accomplished by using established GIS locatingtechnology (e.g., GPS ascertaining a geographically determinableaddress, and assigning the data file to a segment's or intersection'sformal address determined by the system). For example, two or moreaccidents located in an intersection or road segment may have slightlydifferent addresses depending on where within the intersection orsegment the accident location was determined to be. Therefore, thesystem may identify a location based on business rules. In anotherexample business rules may identify an incident location using theaddress of the nearest intersection. In yet another example the systemmay identify the location of an incident on a highway using segmentsbased on mileage markers or the lengths may be dynamically determined bycreating segment lengths based on relatively equal normalized riskvalues. Therefore, roadways that have stretches with higher numbers ofaccidents may have shorter segments than stretches that have feweraccidents. In another example, if the incident occurred in a parkinglot, the entire parking lot may be associated with a formal address thatincludes all accidents located within a determined area. One skilled inthe art will appreciate after review of the entirety disclosed that roadsegment includes a segment of road, a point on a road, and otherdesignations of a location (e.g., an entire parking lot).

For example, an insurance claim-handling processor may collect dataabout numerous incidents such as collision, theft, weather damage, andother events that cause any one of (or combination of) personal injury,vehicle damage, and damage to other vehicles or property. Informationabout the accident may be collected through artifacts such as firstnotice of loss (FNOL) reports and claim adjuster reports and may bestored in one or more data stores used by the insurer. Other data mayalso be collected at the point and time when the incident occurred, andthis information (e.g., weather conditions, traffic conditions, vehiclespeed, etc.) may be stored with the other accident information. Theinformation in these data stores may be distributed by data sources 104,106 in accordance with aspects of the invention. In addition, someinformation may also be recorded in third-party data sources that may beaccessible to one or more insurance companies. For example, trafficinformation (e.g., traffic volume) and weather information may beretrieved in real-time (or near real-time) from their respective datasources.

Referring to FIG. 3, in accordance with aspects of the invention, thecomputing device 102 may send (in step 312) the risk value correspondingto a road segment when it receives location information (in step 302)requesting the risk associated with a particular location. Theparticular location information may be in the form of longitude/latitudecoordinates, street address, intersection, closest address, or otherform of information. Furthermore, in an alternative embodiment theaccuracy of the risk value may be improved by submitting the directionthat a vehicle travels (or may travel) through a road segment. Thecomputing device 102 may receive (in step 304) the vehicle direction anduse it to determine the risk value associated with the vehicle route.For example, a dangerous intersection demonstrates high risk to avehicle/driver that passes through it. However, actuarial analysis(e.g., of data showing many recorded accidents at the location) may showthat it is more dangerous if the driver is traveling northbound on theroad segment and turns left. Therefore, the vehicle direction may alsobe considered when retrieving the appropriate risk value (in step 310).

Likewise, the computing device 102 may also receive (in step 308) otherinformation to enhance the accuracy of the risk value associated with atravel route. For example, the computing device 102 may receive (in step306) the time of day when the driver is driving (or plans to drive)through a particular travel route. This information may improve theaccuracy of the risk value retrieved (in step 310) for the travel route.For example, a particular segment of road through a wilderness area mayhave a higher rate of accidents involving deer during the night hours,but no accidents during the daylight hours. Therefore, the time of daymay also be considered when retrieving the appropriate risk value (instep 310). In addition, the computing device may receive (in step 308)other information to improve the accuracy of the risk value retrieved(in step 310) for a travel route. Some examples of this otherinformation include, but are not limited to, the vehicle's speed (e.g.,a vehicle without a sport suspension attempting to take a dangerouscurve at a high speed), vehicle's speed compared to the posted speedlimit, etc.

In accordance with aspects of the invention, a computer-readable mediumstoring computer-executable instructions for performing the stepsdepicted in FIGS. 2 and 3 and/or described in the present disclosure iscontemplated. The computer-executable instructions may be configured forexecution by a processor (e.g., processor 114 in computing device 102)and stored in a memory (e.g., memory 116 in computing device 102).Furthermore, as explained earlier, the computer-readable medium may beembodied in a non-volatile memory (e.g., in a memory in personalnavigation device 110) or portable media (e.g., CD-ROM, DVD-ROM, USBflash, etc. connected to personal computing device 108).

In accordance with aspects of the invention, a personal navigationdevice 110 may calculate a route risk value for a travel route of avehicle. The personal navigation device 110 may be located, for example,in a driver's vehicle or in a mobile device 112 with location trackingcapabilities. Alternatively, a personal computing device 108 may be usedto calculate the route risk value for a travel route of a vehicle.

For example, referring to FIG. 4, a personal navigation device 110 mayreceive (in step 402) travel route information. The travel routeinformation may include, but is not limited to, a start location, endlocation, road-by-road directions, and/or turn-by-turn directions. Thepersonal navigation device 110 may use the travel route information andmapping software to determine the road segment upon which the vehiclewill travel, and retrieve (in step 404) the risk value for that roadsegment. For each subsequent road segment remaining in the travel route(see step 406), the personal navigation device 110 may access thedatabase of risk values to retrieve (in step 404) the risk value forthat road segment. As explained earlier, the database of risk values maybe stored locally to the personal navigation device 110, or may bestored remotely and accessed through a wired/wireless link to the datastore.

The risk values retrieved (in step 404) for the travel route may beaggregated (in step 408) and a total risk value for the travel route maybe sent (in step 410). In an alternate embodiment, the computing device102 may count the number of each type of road risk along the travelroute based on the values stored in the database. This number may thenbe multiplied by a risk-rating factor for the respective risk type. Arisk type may comprise intersections, locations of past accidents alonga route, railroad crossings, merges, roadway class (residential, local,commercial, rural, highways, limited access highways). Other risk typesmay include proximity to businesses that sell alcohol, churches or bingoparlors.

The sum of this product over all risk types may, in this alternateembodiment, equal the total route risk value. The total route risk valuemay be divided by the distance traveled to determine the route riskcategory for the travel route. For example, a route risk category may beassigned based on a set of route risk value ranges for low, medium, andhigh risk routes.

After being aggregated, the total risk value may be sent (in step 410)to a viewable display on the personal navigation device 110.Alternatively, the total risk value may be sent (in step 410) to alocal/remote memory where it may be recorded and/or monitored. Forexample, it may be desirable for a safe driver to have her total riskvalue for all travel routes traveled over a time period to be uploadedto an insurance company's data store. The insurance company may thenidentify the driver as a lower-risk driver (e.g., a driver that travelson statistically lower-risk routes during lower-risk times) and providethe driver/vehicle with a discount and/or credit (in step 412) on anexisting insurance policy (or towards a future insurance policy). Atleast one benefit of the aforementioned is that safe drivers arerewarded appropriately, while high-risk drivers are treated accordingly.

In some embodiments in accordance with aspects of the invention, theroute risk value sent (in step 410) may be in the form of a numberrating the risk of the travel route (e.g., a rating of 1 to 100 where 1is very low risk and 100 is very high risk). Alternatively, the routerisk value may be in the form of a predetermined category (e.g., lowrisk, medium risk, and high risk). At least one benefit of displayingthe route risk value in this form is the simplicity of the resultingdisplay for the driver. For example, an enhanced GPS unit may display aroute (or segment of a route) in a red color to designate a high riskroute, and a route may be displayed in a green color to designate alower risk route. At least one benefit of a predetermined category forthe route risk value is that it may be used as the means for comparingthe amount of risk associated with each travel route when providingalternate routes. In addition, the enhanced GPS unit may alert thedriver of a high risk road segment and offer the driver an incentive(e.g., monetary incentive, points, etc.) for avoiding that segment.

In accordance with aspects of the invention, a computer-readable mediumstoring computer-executable instructions for performing the stepsdepicted in FIG. 4 and/or described in the present disclosure iscontemplated. The computer-executable instructions may be configured forexecution by a processor (e.g., a processor in personal navigationdevice 110) and stored in a memory (e.g., flash memory in device 110).

When retrieving risk values, in accordance with aspects of theinvention, one or more techniques, either alone or in combination, maybe used for identifying and calculating the appropriate risk value forroad segments. For example, under an accident cost severity rating(ACSR) approach, each point of risk has a value which measures howsevere the average accident is for each point of risk. The value may benormalized and/or scaled by adjusting the range of the values. Forexample, under an ACSR approach using a range of values from 1 to 10:considering all accidents that occur in a predetermined area (e.g., roadsegment, state, zip code, municipality, etc.), the accidents in the topten percentile of expensive accidents in that territory would get a 10value and the lowest 10 percentile of costly accidents in that regionwould get a 1 value. The actual loss cost may be calculated by summingthe various itemized loss costs (e.g., bodily injury, property damage,medical/personal injury protection, collision, comprehensive,uninsured/underinsured motorist, rental reimbursement, towing, etc.).

In an alternate embodiment, the ACSR approach may attribute varyingweights to the different types of loss costs summed to calculate theactual loss cost. For example, after analyzing the information, certainportions of a loss cost (e.g., medical cost) may indicate risk moreaccurately than others. The importance of these portions may be weightedmore heavily in the final loss cost calculation. Actuarial methods maybe used to adjust loss cost data for a segment where a fluke accidentmay cause the calculated risk value to far exceed the risk value basedon all the other data.

Under the accidents per year (APYR) approach, in accordance with aspectsof the invention, each point of risk has a risk value that may reflectthe average number of accidents a year for that individual point ofrisk. Under a modified APYR approach, the risk value for a point of riskcontinues to reflect the average number of accidents a year, butattributes a lesser weight to accidents that occurred a longer time ago,similar to time relevancy validation (e.g., it gives emphasis to recentaccident occurrences over older occurrences).

Under the risk severity (RSR) approach, in accordance with aspects ofthe invention, each point of risk has a risk value that may reflect theseverity of risk for that individual point of risk. For example, anintersection that is a frequent site of vehicle accident related deathsmay warrant a very high risk value under the RSR approach. In oneembodiment, risk severity rating may be based on accident frequency atintersections or in segments over a determined period of time. Inanother embodiment, the rating may be based on loss costs associated tointersections and segments. Yet another embodiment may combine accidentfrequency and severity to form a rating for a segment or intersection.One skilled in the art can recognize that risk severity ratings may bebased on one or a combination of factors associated with intersectionsor segments.

Under the Environmental Risk Variable (ERV) approach, in accordance withaspects of the invention, each point of risk has a risk value that mayreflect any or all information that is not derived from recordedaccidents and/or claims, but that may be the (direct or indirect) causeof an accident. In one embodiment, the risk value under the ERV approachmay be derived from vehicle information transmitted by a data source104, 106. In an alternate embodiment, the EVR approach may use compoundvariables based on the presence or absence of multiple riskconsiderations which are known to frequently, or severely, causeaccidents. A compound variable is one that accounts for the interactionsof multiple risk considerations, whether environmental or derived fromrecorded accidents and/or claims. For example, driving through awildlife crossing zone at dusk would generate a greater risk value thandriving through this same area at noon. The interaction of time of dayand location would be the compound variable. Another example mayconsider current weather conditions, time of day, day of the year, andtopography of the road. A compound variable may be the type ofinfrequent situation which warrants presenting a verbal warning to adriver (e.g., using a speaker system in a personal navigation device 110mounted in a vehicle) of a high risk route (e.g., a high risk roadsegments).

Another possible approach may be to calculate the route risk value usingone or more of the approaches described above divided by the length ofthe route traveled. This may provide an average route risk value for usein conjunction with a mileage rating plan. In one embodiment, the systemcombines route risk and conventional mileage data to calculate risk permile rating.

In one embodiment, a device in a vehicle (e.g., personal navigationdevice 110, mobile device 112, etc.) may record and locally store theroute and/or the route and time during which a route was traveled. Thistravel route information may be uploaded via wireless/wired means (e.g.,cell phones, manually using a computer port, etc.). This travel routeinformation may be used to automatically query a data source 104, 106for route rating information and calculate a total risk value.

Some accident data may be recorded and locally stored on a device (e.g.,personal navigation device 110, mobile device 112, etc.) that providesincident location and a timestamp that can be used to synchronize otherdata located in data sources 104 and 106. The captured information maybe periodically uploaded to computing device 102 for further processingof accident data for updating the road segment database in memory 116.In some embodiments, the other data may include local weatherconditions, vehicle density on the roadway, and traffic signal status.Additional information comprising data from an in-vehicle monitoringsystem (e.g., event data recorder or onboard diagnostic system) mayrecord operational status of the vehicle at the time of the incident.Alternatively, if the vehicle did not have a location tracking device,an insurance claims reporter may enter the address and other informationinto the data source manually. If the vehicle was configured with anin-vehicle monitoring system that has IEEE 802.11 Wi-Fi capabilities (orany other wireless communication capabilities), the travel routeinformation may be periodically uploaded or uploaded in real-time (ornear real-time) via a computer and/or router. The in-vehicle monitoringsystem may be configured to automatically upload travel routeinformation (and other information) through a home wireless router to acomputer. In some advanced monitoring systems, weather and traffic data(and other useful information) may be downloaded (in real-time or nearreal-time) to the vehicle. In some embodiments, it may be desirable touse mobile devices 112 (with the requisite capabilities) to transmit theinformation, provide GPS coordinates, and stream in data from othersources.

The risk types described above may be variables in a multivariate modelof insurance losses, frequencies, severities, and/or pure premiums.Interactions of the variables would also be considered. The coefficientthe model produces for each variable (along with the coefficient for anyinteraction terms) would be the value to apply to each risk type. Thepersonal navigation device 110 may initially provide thequickest/shortest route from a start location A to an end location B,and then determine the route risk value by determining either the sumproduct of the number of each risk type and the value for that risk typeor the overall product of the number of each risk type and the value forthat risk type. (Traffic and weather conditions could either be includedor excluded from the determination of the route risk value forcomparison of routes. If not included, an adjustment may be made to theroute risk value once the route has been traveled). The driver may bepresented with an alternate route which is less risky than the initialroute calculated. The personal navigation device 110 may display thedifference in risk between the alternate routes and permit the driver toselect the preferred route. In some embodiments in accordance with theinvention, a driver/vehicle may be provided a monetary benefit (e.g., acredit towards a future insurance policy) for selecting a less riskyroute.

In one example in accordance with aspects of the invention, a driver mayenter a starting location and an end location into a personal navigationdevice 110. The personal navigation device 110 may present the driverwith an illustrative 2-mile route that travels on a residential roadnear the following risks: 5 intersections, 3 past accident sites, 1railroad crossing, and 1 lane merging site. Assuming for illustrativepurposes that the following risk values apply to the following risktypes:

Risk Type Risk-rating Factor Intersections 55 Past Accidents 30 RailroadCrossing 5 Merge 60 Residential Road 2 per mile

Then, the route risk value for the entire 2-mile route may becalculated, in one embodiment of the invention, as follows:

Risk Type Risk-rating Factor Count Product Intersections 55 5 55 * 5 =275 Past Accidents 30 3 30 * 3 = 90  Railroad Crossing  5 1  5 * 1 = 5 Merge 60 1 60 * 1 = 60  Residential Road 2 per mile 2  2 * 2 = 4  SumTotal 434

Assuming a route risk value between 0 and 350 (per mile) is categorizedas a low-risk route, then the aforementioned 2-mile route's risk valueof 217 (i.e., 434 divided by 2) classifies it a low-risk route.

In some embodiments, for rating purposes the route risk value mayconsider the driving information of the driver/vehicle. For example, thepersonal navigation device 110 (or other device) may record the routetaken, as well as the time of day/month/year, weather conditions,traffic conditions, and the actual speed driven compared to the postedspeed limit. The current weather and traffic conditions may be recordedfrom a data source 104, 106. Weather conditions and traffic conditionsmay be categorized to determine the risk type to apply. The posted speedlimits may be included in the geographic information. For each segmentof road with a different posted speed limit, the actual speed driven maybe compared to the posted speed limit. The difference may be averagedover the entire distance of the route. In addition, various techniquesmay be used to handle the amount of time stopped in traffic, at trafficlights, etc. One illustrative technique may be to only count the amountof time spent driving over the speed limit and determine the averagespeed over the speed limit during that time. Another illustrative methodmay be to exclude from the total amount of time the portion where thevehicle is not moving. Then, upon completion of the trip, the route riskvalue may be calculated and stored in memory along with the otherinformation related to the route risk score and mileage traveled. Thisinformation may later be transmitted to an insurance company's datastore, as was described above.

In another embodiment in accordance with aspects of the invention, realtime data may be used to dynamically assign risk values to each point ofrisk. For example, some road segments may have a higher risk value whena vehicle travels through at a time when, e.g., snowfall is heavy. Insuch situations, a dynamic risk value may be applied to the road segmentto determine the appropriate route risk value to assign to the route.

Referring to FIG. 5, in accordance with aspects of the invention, amethod of selling a vehicular insurance policy is illustrated. A vehicleowner or driver may be provided (in step 502) with an insurance policywith a total risk score. The total risk score (e.g., 500) indicates thequantity of risk the vehicle is permitted to travel through before theinsurance policy must be renewed or becomes terminated. For example, asthe vehicle is driven over various travel routes, the route risk valuesfor the road segments traveled are deducted (in step 504) from the totalrisk score of the insurance policy. The vehicle owner and/or driver maybe provided (in step 506) an option to renew the insurance policy (e.g.,to purchase additional risk points to apply towards the total risk scoreof the insurance policy). Once the total risk score falls to zero orunder (see step 508), the vehicle owner and/or driver (or any otherperson/entity authorized to renew the policy) is provided (in step 510)with a final option to renew the insurance policy before the insurancepolicy terminates (in step 512). It will be apparent to one skilled inthe art after review of the entirety disclosed that the embodimentillustrated above may benefit from a personal navigation device 110 (orsimilar device) to monitor and record the route traveled by a vehicle.At least one benefit of the insurance policy illustrated by FIG. 5 isthe ability to pay per quantity of risk consumed instead of paying onlya fixed premium.

In another embodiment in accordance with aspects of the invention,route-dependent pricing uses route risk values to adjust insurancepricing based on where a vehicle is driven. Contrary to the embodimentabove where the vehicle's insurance policy terminated dependent on thequantity of risk consumed by the vehicle's travel route, in thisembodiment, an insurance company (or its representatives, e.g., agent)may adjust the price quoted/charged for an insurance policy based onrisk consumed. In this embodiment, a vehicle/driver may be categorizedinto a risk class (e.g., low-risk, medium-risk, high risk, etc.) andcharged for insurance accordingly. For example, the vehicle/driver maybe provided with notification of a credit/debit if the vehicle consumedless/more, respectively, of risk at the end of a policy term than wasinitially purchased.

In another embodiment: the insurance policy is sold and priced in partbased on where a customer falls within a three sigma distribution ofrisk units consumed by all insured per a typical policy period. Thepolicy pricing may be based on an initial assumption of risk to beconsumed in the prospective policy period or may be based on riskconsumed in a preceding policy period. In a case where the number ofrisk units consumed is greater than estimated, the customer may bebilled for the overage at the end of (or during) the policy period. Inyet another embodiment, the system may be provided as a pay-as-you-drivecoverage where the customer is charged in part based on the actual riskunits consumed in the billing cycle. The system may include a telematicsdevice that monitors, records, and periodically transmits theconsumption of risk units to processor 114 that may automatically billor deduct the cost from an account.

While the invention has been described with respect to specific examplesincluding presently exemplary modes of carrying out the invention, thoseskilled in the art will appreciate that there are numerous variationsand permutations of the above-described systems and techniques that fallwithin the spirit and scope of the invention.

We claim:
 1. A method, comprising: receiving, from a first processor incommunication with a location detection unit located in a vehicle, atravel route of the vehicle; retrieving, by a second processor incommunication over at least a wireless network with the first processor,a segment value for each of a plurality of road segments correspondingto the travel route of the vehicle, wherein each segment value is basedat least on accident information corresponding to each of the pluralityof road segments, wherein the accident information comprises accidentloss information and direction of travel at accident location;aggregating segment values, by the second processor, to calculate aroute value for the travel route of the vehicle; and sending, by thesecond processor over the at least a wireless network to the firstprocessor located in the vehicle, the route value for the travel routeof the vehicle.
 2. The method of claim 1, wherein accident informationcomprises number of vehicle accidents.
 3. The method of claim 1, whereinaccident information comprises at least one of: vehicle direction attime of damage, accident time, and accident date.
 4. The method of claim1, wherein the route value is a predetermined risk category comprised oflow, medium, and high.
 5. The method of claim 1, wherein each segmentvalue is further based at least on accident location informationcorresponding to each of the plurality of road segments.
 6. The methodof claim 1, in response to receiving, by the second processor, a requestfor a risk value associated with a particular location, sending, by thesecond processor over the at least a wireless network to the firstprocessor located in the vehicle, a value associated with a road segmentcontaining the particular location.
 7. The method of claim 1, whereinthe vehicle is associated with a vehicle insurance policy, the methodcomprising: calculating, by the second processor, a total risk score forthe travel route of the vehicle based on the aggregated segment values;and adjusting a cost of the vehicle insurance policy for the vehiclebased on the route value, wherein the adjusting is further based atleast in part on the total risk score.
 8. The method of claim 7, whereinthe vehicle is designated in a predetermined class based on a total riskscore, and the adjusting of the cost is further based at least in parton the predetermined class.
 9. The method of claim 7, comprising:transmitting, by the second processor, a notification to a policyholderof the vehicle insurance policy of a credit based on the cost of thevehicle insurance policy is less after the adjusting.
 10. The method ofclaim 7, comprising: generating a notification, by the second processor,of an option to renew the vehicle insurance policy before terminatingthe vehicle insurance policy; and displaying in the vehicle, by thefirst processor, the generated notification of the option to renew thevehicle insurance policy.
 11. The method of claim 7, comprising:receiving, at the second processor, geographic information correspondingto the plurality of road segments; and wherein the calculating of thetotal risk score is further based at least in part on the geographicinformation.
 12. The method of claim 1, comprising: in response toreceiving a request for a risk value associated with a particular roadsegment of the plurality of road segments, sending, by the secondprocessor, a value associated with the road segment considering vehicledirection through the particular road segment.
 13. The method of claim1, wherein the route value is calculated using an accident cost severityrating approach.
 14. A system comprising: a location detection unit,located in a vehicle, configured to detect locations of the vehiclecomprising at least a start location and an end location; a firstprocessor in communication with the location detection unit; a secondprocessor in communication over at least a wireless network with thefirst processor; a computer memory storing instructions that, whenexecuted by the second processor, causes the system to: receive, fromthe first processor in communication with the location detection unitlocated in the vehicle, a travel route of the vehicle; retrieving, bythe second processor in communication over at least a wireless networkwith the first processor, a segment value for each of a plurality ofroad segments corresponding to the travel route of the vehicle, whereineach segment value is based at least on accident informationcorresponding to each of the plurality of road segments, wherein theaccident information comprises accident loss information and directionof travel at accident location; aggregating segment values, by thesecond processor, to calculate a route value for the travel route of thevehicle; and sending, by the second processor over the at least awireless network to the first processor located in the vehicle, theroute value for the travel route of the vehicle.
 15. The system of claim14, wherein the vehicle is associated with a vehicle insurance policy,and wherein the computer memory stores instructions that, when executedby the second processor, further causes the system to: calculate, by thesecond processor, a total risk score for the travel route of the vehiclebased on the aggregated segment values; adjust a cost of the vehicleinsurance policy for the vehicle based on the route value, wherein theadjusting is further based at least in part on the total risk score; andbased on the safety risk score of the route, debit an account associatedwith the vehicle insurance policy.
 16. The system of claim 14, whereinthe computer memory stores instructions that, when executed by thesecond processor, further causes the system to: in response toreceiving, by the second processor, a request for a risk valueassociated with a particular location detected by the locationdetermination unit, send, by the second processor over the at least awireless network to the first processor located in the vehicle, a valueassociated with a road segment containing the particular location.
 17. Anon-transitory computer-readable memory storing computer-executableinstructions that when executed by a processor, causes the processor to:receive, from a location detection unit located in a vehicle, a travelroute of the vehicle; retrieve, over at least a wireless network, asegment value for each of a plurality of road segments corresponding tothe travel route of the vehicle, wherein each segment value is based atleast on accident information corresponding to each of the plurality ofroad segments, wherein the accident information comprises accident lossinformation and direction of travel at accident location; aggregatesegment values to calculate a route value for the travel route of thevehicle; and send, over the at least a wireless network, the route valuefor the travel route of the vehicle.